Description:
This work is a comprehensive study of the field. It provides an
entry point to the novice willing to move in the research field
reconfigurable computing, FPGA and system on programmable chip
design. The book can also be used as teaching reference for a
graduate course in computer engineering, or as reference to
advance electrical and computer engineers. It provides a very
strong theoretical and practical background to the field, from
the early Estrin’s machine to the very modern architecture such
as embedded logic devices.

Editorial Reviews

New technologies have enabled us to collect massive amounts of data in many fields. However, our pace of discovering useful information and knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains a comprehensive set of data mining algorithms from various data mining fields. The book reviews theoretical rationales and procedural details of data mining algorithms, including those commonly found in the literature and those presenting considerable difficulty, using small data examples to explain and walk through the algorithms.

The book covers a wide range of data mining algorithms, including those commonly found in data mining literature and those not fully covered in most of existing literature due to their considerable difficulty. The book presents a list of software packages that support the data mining algorithms, applications of the data mining algorithms with references, and exercises, along with the solutions manual and PowerPoint slides of lectures.

The author takes a practical approach to data mining algorithms so that the data patterns produced can be fully interpreted. This approach enables students to understand theoretical and operational aspects of data mining algorithms and to manually execute the algorithms for a thorough understanding of the data patterns produced by them.

Description:
New technologies have enabled us to collect massive amounts of
data in many fields. However, our pace of discovering useful
information and knowledge from these data falls far behind our
pace of collecting the data. Data Mining: Theories,
Algorithms, and Examples introduces and explains a
comprehensive set of data mining algorithms from various data
mining fields. The book reviews theoretical rationales and
procedural details of data mining algorithms, including those
commonly found in the literature and those presenting
considerable difficulty, using small data examples to explain and
walk through the algorithms.

Description:
New technologies have enabled us to collect massive amounts of
data in many fields. However, our pace of discovering useful
information and knowledge from these data falls far behind our
pace of collecting the data. Data Mining: Theories,
Algorithms, and Examples introduces and explains a
comprehensive set of data mining algorithms from various data
mining fields. The book reviews theoretical rationales and
procedural details of data mining algorithms, including those
commonly found in the literature and those presenting
considerable difficulty, using small data examples to explain and
walk through the algorithms.

Description:
This book is concentrated on the synergy between computer science
and numerical analysis. It is written to provide a firm
understanding of the described approaches to computer scientists,
engineers or other experts who have to solve real problems. The
meshless solution approach is described in more detail, with a
description of the required algorithms and the methods that are
needed for the design of an efficient computer program. Most of
the details are demonstrated on solutions of practical problems,
from basic to more complicated ones. This book will be a useful
tool for any reader interested in solving complex problems in… more…

Description: This volume presents the proceedings of the Seventh International
Workshop on Computational Geometry, CG'91, held at the University
of Berne, Switzerland, March 21/22, 1991. Computational geometry is
not a precisely defined field. Often, it is understood as a nearly
mathematical discipline, dealing mainly with complexity questions
concerning geometrical problems and algorithms. But often too, and
perhaps increasingly, questions of more practical relevance are
central, such as applicability, numerical behavior and performance
for all kinds of input size. Topics considered in CG'91 include: –
Generalizations and applications of the Voronoi diagram -… more…

Description: Adaptive Signal Models: Theory, Algorithms and Audio
Applications presents methods for deriving mathematical models
of natural signals. The introduction covers the fundamentals of
analysis-synthesis systems and signal representations. Some of the
topics in the introduction include perfect and near-perfect
reconstruction, the distinction between parametric and
nonparametric methods, the role of compaction in signal modeling,
basic and overcomplete signal expansions, and time-frequency
resolution issues. These topics arise throughout the book as do a
number of other topics such as filter banks and
multiresolution.
The second chapter gives a detailed… more…